Dual substrate limitation modeling and implications for mainstream deammonification.

Area of Science:

• Environmental microbiology
• Biochemical engineering
• Wastewater treatment technologies

Background:

• Substrate limitation is common in wastewater treatment, necessitating accurate microbial behavior models.
• Monod kinetics are standard for single-substrate limitation, but models for multiple limitations vary.
• Understanding dual limitation is key for designing and optimizing biokinetic models.

Purpose of the Study:

• To compare three dual limitation models: multiplicative, minimum, and Bertolazzi.
• To evaluate model performance using experimental data from nitrite-oxidizing and anaerobic ammonia-oxidizing bacteria.
• To assess the impact of model selection on deammonification process simulations.

Main Methods:

• Experiments were conducted on nitrite-oxidizing bacteria and anaerobic ammonia-oxidizing bacteria (Anammox) from deammonification pilots.
• Deterministic likelihood-based parameter estimation and Bayesian inference were used for parameter estimation.
• Model performance was evaluated through parameter estimation accuracy and simulation of experimental observations.

Main Results:

• The minimum model demonstrated superior performance compared to the multiplicative and Bertolazzi models.
• Parameters estimated using the minimum model closely matched those from single limitation tests.
• Simulations using the minimum model best represented experimental data, regardless of parameter estimation method.

Conclusions:

• The minimum dual limitation model is recommended for accurately describing microbial kinetics in wastewater treatment.
• Model selection significantly impacts process performance predictions, with potential for 75% variation in deammonification systems.
• Accurate modeling of dual substrate limitation is vital for effective wastewater treatment design and optimization.